Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.
| additional remarks |
This lab gives participating students a chance to learn relevant computer science techniques used in Energy Informatics (EI). Energy informatics deals with enabling higher energy efficiency and the integration of fluctuating renewable energy sources into power systems.
The lab is organized as a series of different tasks, each of which will require the application of a tool or technique to solving an EI problem. Tasks include the following:
• Smart Grid simulation using GridLab-D
• Modelling and solving generator dispatch optimization problems with Matlab
• Modelling and solving optimal power flow problems with Matlab
• Power Grid simulation using DigSilent Power Factory
• Machine learning based prediction using various tools, e.g., WEKA and python library
• Non-intrusive load monitoring using signal processing and machine learning
• Crowdsourcing experiments using OpenGridMap
• Data-driven analysis of strategic decisions using iPython notebook |
| Links |
E-Learning course (e. g. Moodle)
TUMonline entry
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